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This detailed survey of the ontology modelling application Knowledge Seeker demonstrates how it can improve the efficiency of traditional information systems, increase the accuracy of text classification, and enhance the capabilities of search engines.
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Description du livre Hardcover. Etat : new. N° de réf. du vendeur 9783642179150
Description du livre Etat : New. N° de réf. du vendeur ABLIING23Mar3113020220107
Description du livre Etat : New. PRINT ON DEMAND Book; New; Fast Shipping from the UK. No. book. N° de réf. du vendeur ria9783642179150_lsuk
Description du livre Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The Knowledge Seeker is a useful system to develop various intelligent applications such as ontology-based search engine, ontology-based text classification system, ontological agent system, and semantic web system etc. The Knowledge Seeker contains four different ontological components. First, it defines the knowledge representation model ¡V Ontology Graph. Second, an ontology learning process that based on chi-square statistics is proposed for automatic learning an Ontology Graph from texts for different domains. Third, it defines an ontology generation method that transforms the learning outcome to the Ontology Graph format for machine processing and also can be visualized for human validation. Fourth, it defines different ontological operations (such as similarity measurement and text classification) that can be carried out with the use of generated Ontology Graphs. The final goal of the KnowledgeSeeker system framework is that it can improve the traditional information system with higher efficiency. In particular, it can increase the accuracy of a text classification system, and also enhance the search intelligence in a search engine. This can be done by enhancing the system with machine processable ontology. The KnowledgeSeeker is a useful system to develop various intelligent applications such as ontology-based search engine, ontology-based text classification system, ontological agent system, and semantic web system etc. The KnowledgeSeeker contains four different ontological components. First, it defines the knowledge representation model ¡V Ontology Graph. Second, an ontology learning process that based on chi-square statistics is proposed for automatic learning an Ontology Graph from texts for different domains. Third, it defines an ontology generation method that transforms the learning outcome to the Ontology Graph format for machine processing and also can be visualized for human validation. Fourth, it defines different ontological operations (such as similarity measurement and text classification) that can be carried out with the use of generated Ontology Graphs. The final goal of the KnowledgeSeeker system framework is that it can improve the traditional information system with higher efficiency. In particular, it can increase the accuracy of a text classification system, and also enhance the search intelligence in a search engine. This can be done by enhancing the system with machine processable ontology. 264 pp. Englisch. N° de réf. du vendeur 9783642179150
Description du livre Gebunden. Etat : New. N° de réf. du vendeur 5051584
Description du livre Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - The Knowledge Seeker is a useful system to develop various intelligent applications such as ontology-based search engine, ontology-based text classification system, ontological agent system, and semantic web system etc. The Knowledge Seeker contains four different ontological components. First, it defines the knowledge representation model ¡V Ontology Graph. Second, an ontology learning process that based on chi-square statistics is proposed for automatic learning an Ontology Graph from texts for different domains. Third, it defines an ontology generation method that transforms the learning outcome to the Ontology Graph format for machine processing and also can be visualized for human validation. Fourth, it defines different ontological operations (such as similarity measurement and text classification) that can be carried out with the use of generated Ontology Graphs. The final goal of the KnowledgeSeeker system framework is that it can improve the traditional information system with higher efficiency. In particular, it can increase the accuracy of a text classification system, and also enhance the search intelligence in a search engine. This can be done by enhancing the system with machine processable ontology. The KnowledgeSeeker is a useful system to develop various intelligent applications such as ontology-based search engine, ontology-based text classification system, ontological agent system, and semantic web system etc. The KnowledgeSeeker contains four different ontological components. First, it defines the knowledge representation model ¡V Ontology Graph. Second, an ontology learning process that based on chi-square statistics is proposed for automatic learning an Ontology Graph from texts for different domains. Third, it defines an ontology generation method that transforms the learning outcome to the Ontology Graph format for machine processing and also can be visualized for human validation. Fourth, it defines different ontological operations (such as similarity measurement and text classification) that can be carried out with the use of generated Ontology Graphs. The final goal of the KnowledgeSeeker system framework is that it can improve the traditional information system with higher efficiency. In particular, it can increase the accuracy of a text classification system, and also enhance the search intelligence in a search engine. This can be done by enhancing the system with machine processable ontology. N° de réf. du vendeur 9783642179150
Description du livre Hardcover. Etat : Brand New. 264 pages. 9.25x6.25x0.75 inches. In Stock. N° de réf. du vendeur x-3642179150
Description du livre Etat : New. This detailed survey of the ontology modelling application Knowledge Seeker demonstrates how it can improve the efficiency of traditional information systems, increase the accuracy of text classification, and enhance the capabilities of search engines. Series: Intelligent Systems Reference Library. Num Pages: 263 pages, biography. BIC Classification: UYQE. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 20. Weight in Grams: 609. . 2011. Hardback. . . . . N° de réf. du vendeur V9783642179150
Description du livre Etat : New. This detailed survey of the ontology modelling application Knowledge Seeker demonstrates how it can improve the efficiency of traditional information systems, increase the accuracy of text classification, and enhance the capabilities of search engines. Series: Intelligent Systems Reference Library. Num Pages: 263 pages, biography. BIC Classification: UYQE. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 20. Weight in Grams: 609. . 2011. Hardback. . . . . Books ship from the US and Ireland. N° de réf. du vendeur V9783642179150